Bibliography

Abbott, Benjamin P., Richard Abbott, TD Abbott, et al. 2016. “Observation of Gravitational Waves from a Binary Black Hole Merger.” Physical Review Letters 116 (6): 061102.

Akiyama, Kazunori, Antxon Alberdi, Walter Alef, et al. 2019. “First M87 Event Horizon Telescope Results. IV. Imaging the Central Supermassive Black Hole.” The Astrophysical Journal Letters 875 (1): L4.

Balli, Hatice Ozer, and Bent E. Sørensen. 2013. “Interaction Effects in Econometrics.” Empirical Economics 45 (1): 583–603.

Bantilan, Niels. 2020. “Pandera: Statistical Data Validation of Pandas Dataframes.” In Proceedings of the 19th Python in Science Conference, edited by Meghann Agarwal, Chris Calloway, Dillon Niederhut, and David Shupe. https://doi.org/ 10.25080/Majora-342d178e-010 .

Bellemare, Marc F. 2020. “How to Write Applied Papers in Economics.” Working Paper. http://marcfbellemare.com/wordpress/wp-content/uploads/2020/09/BellemareHowToPaperSeptember2020.pdf.

Bellemare, Marc F., and Casey J. Wichman. 2020. “Elasticities and the Inverse Hyperbolic Sine Transformation.” Oxford Bulletin of Economics and Statistics 82 (1): 50–61.

Betancourt, Michael. 2018. “A Conceptual Introduction to Hamiltonian Monte Carlo.” arXiv, no. 1701.02434.

Bielajew, Alex F. 2001. Fundamentals of the Monte Carlo Method for Neutral and Charged Particle Transport. Vol. 1. The University of Michigan.

Boeing, Geoff. 2017. “OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks.” Computers, Environment and Urban Systems 65: 126–39.

Bradbury, James, Roy Frostig, Peter Hawkins, et al. 2018. “JAX: Composable Transformations of Python+NumPy Programs.” None. http://github.com/google/jax.

Brauner, Jan M., Sören Mindermann, Mrinank Sharma, et al. 2021. “Inferring the Effectiveness of Government Interventions Against COVID-19.” Science 371 (6531): eabd9338.

Broman, Karl W., and Kara H. Woo. 2018. “Data Organization in Spreadsheets.” The American Statistician 72 (1): 2–10.

Brown, Jessica H. 2022. “The Tradeoff Between Knowledge of Mandated Benefits and Moral Hazard.” Southern Economic Journal 88 (3): 1037–64.

Cattaneo, Matias D., Richard K. Crump, Max H. Farrell, and Yingjie Feng. 2019. “On Binscatter.” arXiv Preprint arXiv:1902.09608.

Cook, Lisa D. 2011. “Inventing Social Capital: Evidence from African American Inventors, 1843–1930.” Explorations in Economic History 48 (4): 507–18.

Diez, David M., Christopher D. Barr, and Mine Cetinkaya-Rundel. 2012. OpenIntro Statistics. OpenIntro.

Galli, Soledad. 2022. Python Feature Engineering Cookbook: Over 70 Recipes for Creating, Engineering, and Transforming Features to Build Machine Learning Models. Packt Publishing Ltd.

Hand, David J. 2020. Dark Data: Why What You Don’t Know Matters. Princeton University Press.

Hastie, Trevor, Robert Tibshirani, Jerome H. Friedman, and Jerome H. Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Vol. 2. Springer.

Horst, Allison Marie, Alison Presmanes Hill, and Kristen B. Gorman. 2020. “Palmerpenguins: Palmer Archipelago (Antarctica) Penguin Data.” R Package Version 0.1.0.

Hunter, John D. 2007. “Matplotlib: A 2D Graphics Environment.” Computing in Science & Engineering 9 (03): 90–95.

Koenker, Roger, and Kevin F. Hallock. 2001. “Quantile Regression.” Journal of Economic Perspectives 15 (4): 143–56.

Lauridsen, Charlotte, Søren Højsgaard, and Martin Tang Sørensen. 1999. “Influence of Dietary Rapeseed Oil, Vitamin e, and Copper on the Performance and the Antioxidative and Oxidative Status of Pigs.” Journal of Animal Science 77 (4): 906–16.

McInnes, Leland, John Healy, and James Melville. 2018. “Umap: Uniform Manifold Approximation and Projection for Dimension Reduction.” arXiv Preprint arXiv:1802.03426.

Nuñez, Jamie R., Christopher R. Anderton, and Ryan S. Renslow. 2018. “Optimizing Colormaps with Consideration for Color Vision Deficiency to Enable Accurate Interpretation of Scientific Data.” PloS One 13 (7): e0199239.

Orben, Amy, and Andrew K. Przybylski. 2019. “The Association Between Adolescent Well-Being and Digital Technology Use.” Nature Human Behaviour 3 (2): 173–82.

Ravuri, Suman, Karel Lenc, Matthew Willson, et al. 2021. “Skillful Precipitation Nowcasting Using Deep Generative Models of Radar.” Nature 597: 672–77.

Rougier, Nicolas. 2021. Scientific Visualization: Python + Matplotlib. HAL Open Science.

Rubinstein, Reuven Y., and Dirk P. Kroese. 2016. Simulation and the Monte Carlo Method. Vol. 10. John Wiley & Sons.

Salvatier, John, Thomas V. Wiecki, and Christopher Fonnesbeck. 2016. “Probabilistic Programming in Python Using PyMC3.” PeerJ Computer Science 2: e55.

Schoot, Rens van de, Sarah Depaoli, Ruth King, et al. 2021. “Bayesian Statistics and Modelling.” Nature Reviews Methods Primers 1 (1): 1–26.

Schwabish, Jonathan. 2021. Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks. Columbia University Press.

Sheppard, Kevin. 2012. “Introduction to Python for Econometrics, Statistics and Data Analysis.” Self-Published, University of Oxford. https://www.kevinsheppard.com/files/teaching/python/notes/python_introduction_2020.pdf.

Silberzahn, Raphael, Eric L. Uhlmann, Daniel P. Martin, et al. 2018. “Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results.” Advances in Methods and Practices in Psychological Science 1 (3): 337–56.

Simonsohn, Uri, Joseph P. Simmons, and Leif D. Nelson. 2020. “Specification Curve Analysis.” Nature Human Behaviour 4 (11): 1208–14.

Vallat, Raphael. 2018. “Pingouin: Statistics in Python.” Journal of Open Source Software 3 (31): 1026.

White, Elwyn Brooks, and William Strunk. 1972. The Elements of Style. Macmillan New York.

Zinsser, William. 2006. “On Writing Well: The Classic Guide to Writing Nonfiction.” New York, NY.